Privacy

The “PreCheck” program is billed as a convenient service to allow U.S.
travelers to “speed through
security” at airports. However, the latest
proposal released by the Transportation Security Administration (TSA)
reveals the Department of Homeland Security’s greater underlying plan to
collect face images and iris scans on a nationwide scale. DHS’s programs
will become a massive violation of privacy that could serve as a gateway to
the collection of biometric data to identify and track every traveler at
every airport and border crossing in the country.

Cameras concealed within the screen will track the make, model and colour
of passing cars to deliver more targeted adverts. Brands can even
pre-program triggers so that specific adverts are played when a certain
model of car passes the screen, according to Landsec, the company the owns the screens.

Tech

With recent speeches in both Silicon Valley and China, Jeff Dean, one of Google’s
leading engineers, spotlighted a Google project called AutoML. ML is
short for machine learning, referring to computer algorithms that can learn
to perform particular tasks on their own by analyzing data. AutoML, in turn,
is a machine-learning algorithm that learns to build other machine-learning
algorithms.

With it, Google may soon find a way to create A.I. technology that can
partly take the humans out of building the A.I. systems that many believe
are the future of the technology industry.

If you imagine the life of a machine learning researcher, you might think
it’s quite glamorous. You’ll program self-driving cars, work for the biggest
names in tech, and your software could even lead to the downfall
of humanity. So cool! But, as a new survey of data scientists and
machine learners shows, those expectations need adjusting, because the
biggest challenge in these professions is something quite mundane: cleaning
dirty data.

This comes from a survey conducted by data
science community Kaggle (which was acquired by Google earlier this
year). Some 16,700 of the site’s 1.3 million members responded to the
questionnaire, and when asked about the biggest barriers faced at work, the
most common answer was “dirty data,” followed by a lack of talent in the
field.

As a young programmer, Joshua Browder built a
chatbot to act as a kind of AI lawyer that would help people dispute
parking tickets. Not only did it work, but it was hugely popular, which led
Browder to expand the program to help
anyone harmed by the Equifax scandal sue the company in small claims
court. Now his company, DoNotPay, is aiming even higher: by the end of this
year, Browder plans to launch an addition to the platform that will you let
you sue anyone.